{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T18:17:22Z","timestamp":1790965042626,"version":"4.1.0"},"reference-count":47,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2023,10,5]],"date-time":"2023-10-05T00:00:00Z","timestamp":1696464000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000265","name":"Medical Research Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000265","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100014013","name":"UK Research and Innovation","doi-asserted-by":"publisher","award":["MR\/V028448"],"award-info":[{"award-number":["MR\/V028448"]}],"id":[{"id":"10.13039\/100014013","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010089","name":"JGW Patterson Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100010089","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Cytometry Pt A"],"published-print":{"date-parts":[[2024,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Analysis of imaging mass cytometry (IMC) data and other low\u2010resolution multiplexed tissue imaging technologies is often confounded by poor single\u2010cell segmentation and suboptimal approaches for data visualization and exploration. This can lead to inaccurate identification of cell phenotypes, states, or spatial relationships compared to reference data from single\u2010cell suspension technologies. To this end we have developed the \u201c\n                    <jats:styled-content style=\"fixed-case\">OPTimized<\/jats:styled-content>\n                    Imaging Mass cytometry\n                    <jats:styled-content style=\"fixed-case\">AnaLysis<\/jats:styled-content>\n                    (OPTIMAL)\u201d framework to benchmark any approaches for cell segmentation, parameter transformation, batch effect correction, data visualization\/clustering, and spatial neighborhood analysis. Using a panel of 27 metal\u2010tagged antibodies recognizing well\u2010characterized phenotypic and functional markers to stain the same Formalin\u2010Fixed Paraffin Embedded (FFPE) human tonsil sample tissue microarray over 12 temporally distinct batches we tested several cell segmentation models, a range of different\n                    <jats:italic>arcsinh<\/jats:italic>\n                    cofactor parameter transformation values, 5 different dimensionality reduction algorithms, and 2 clustering methods. Finally, we assessed the optimal approach for performing neighborhood analysis. We found that single\u2010cell segmentation was improved by the use of an Ilastik\u2010derived probability map but that issues with poor segmentation were only really evident after clustering and cell type\/state identification and not always evident when using \u201cclassical\u201d bivariate data display techniques. The optimal\n                    <jats:italic>arcsinh<\/jats:italic>\n                    cofactor for parameter transformation was 1 as it maximized the statistical separation between negative and positive signal distributions and a simple\n                    <jats:italic>Z<\/jats:italic>\n                    \u2010score normalization step after\n                    <jats:italic>arcsinh<\/jats:italic>\n                    transformation eliminated batch effects. Of the five different dimensionality reduction approaches tested, PacMap gave the best data structure with FLOWSOM clustering out\u2010performing phenograph in terms of cell type identification. We also found that neighborhood analysis was influenced by the method used for finding neighboring cells with a \u201cdisc\u201d pixel expansion outperforming a \u201cbounding box\u201d approach combined with the need for filtering objects based on size and image\u2010edge location. Importantly, OPTIMAL can be used to assess and integrate with any existing approach to IMC data analysis and, as it creates .FCS files from the segmentation output and allows for single\u2010cell exploration to be conducted using a wide variety of accessible software and algorithms familiar to conventional flow cytometrists.\n                  <\/jats:p>","DOI":"10.1002\/cyto.a.24803","type":"journal-article","created":{"date-parts":[[2023,9,26]],"date-time":"2023-09-26T04:17:13Z","timestamp":1695701833000},"page":"36-53","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["<scp>OPTIMAL<\/scp>\n                    : An\n                    <scp>OPTimized<\/scp>\n                    Imaging Mass cytometry\n                    <scp>AnaLysis<\/scp>\n                    framework for benchmarking segmentation and data exploration"],"prefix":"10.1002","volume":"105","author":[{"given":"Bethany","family":"Hunter","sequence":"first","affiliation":[{"name":"Flow Cytometry Core Facility, Faculty of Medical Sciences Newcastle University  Newcastle upon Tyne UK"},{"name":"Biosciences Institute, Innovation, Methodology and Application (IMA) Research Theme, Faculty of Medical Sciences Newcastle University  Newcastle upon Tyne UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ioana","family":"Nicorescu","sequence":"additional","affiliation":[{"name":"Translational and Clinical Research Institute, Immunity and Inflammation Theme, Faculty of Medical Sciences Newcastle University  Newcastle upon Tyne UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emma","family":"Foster","sequence":"additional","affiliation":[{"name":"Image Analysis Unit, Faculty of Medical Sciences Newcastle University  Newcastle upon Tyne UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"McDonald","sequence":"additional","affiliation":[{"name":"Flow Cytometry Core Facility, Faculty of Medical Sciences Newcastle University  Newcastle upon Tyne UK"},{"name":"Biosciences Institute, Innovation, Methodology and Application (IMA) Research Theme, Faculty of Medical Sciences Newcastle University  Newcastle upon Tyne UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gillian","family":"Hulme","sequence":"additional","affiliation":[{"name":"Flow Cytometry Core Facility, Faculty of Medical Sciences Newcastle University  Newcastle upon Tyne UK"},{"name":"Biosciences Institute, Innovation, Methodology and Application (IMA) Research Theme, Faculty of Medical Sciences Newcastle University  Newcastle upon Tyne UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew","family":"Fuller","sequence":"additional","affiliation":[{"name":"Flow Cytometry Core Facility, Faculty of Medical Sciences Newcastle University  Newcastle upon Tyne UK"},{"name":"Biosciences Institute, Innovation, Methodology and Application (IMA) Research Theme, Faculty of Medical Sciences Newcastle University  Newcastle upon Tyne UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amanda","family":"Thomson","sequence":"additional","affiliation":[{"name":"Flow Cytometry Core Facility, Faculty of Medical Sciences Newcastle University  Newcastle upon Tyne UK"},{"name":"Translational and Clinical Research Institute, Immunity and Inflammation Theme, Faculty of Medical Sciences Newcastle University  Newcastle upon Tyne UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thibaut","family":"Goldsborough","sequence":"additional","affiliation":[{"name":"School of Informatics University of Edinburgh  Edinburgh UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Catharien M. U.","family":"Hilkens","sequence":"additional","affiliation":[{"name":"Translational and Clinical Research Institute, Immunity and Inflammation Theme, Faculty of Medical Sciences Newcastle University  Newcastle upon Tyne UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joaquim","family":"Majo","sequence":"additional","affiliation":[{"name":"Cellular Pathology, Newcastle upon Tyne Hospitals NHS Foundation Trust  Newcastle upon Tyne UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luke","family":"Milross","sequence":"additional","affiliation":[{"name":"Transplantation and Regenerative Medicine, Newcastle University Translational and Clinical Research Institute, Faculty of Medical Sciences Newcastle University  Newcastle upon Tyne UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew","family":"Fisher","sequence":"additional","affiliation":[{"name":"Transplantation and Regenerative Medicine, Newcastle University Translational and Clinical Research Institute, Faculty of Medical Sciences Newcastle University  Newcastle upon Tyne UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peter","family":"Bankhead","sequence":"additional","affiliation":[{"name":"Centre for Genomic and Experimental Medicine, CRUK Scotland Centre, and Edinburgh Pathology University of Edinburgh  Edinburgh UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4347-5394","authenticated-orcid":false,"given":"John","family":"Wills","sequence":"additional","affiliation":[{"name":"Department of Veterinary Medicine Cambridge University  Cambridge UK"},{"name":"Department of Biomedical Engineering Swansea University  Swansea, Wales UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paul","family":"Rees","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering Swansea University  Swansea, Wales UK"},{"name":"Imaging Platform Broad Institute of MIT and Harvard  Cambridge Massachusetts USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew","family":"Filby","sequence":"additional","affiliation":[{"name":"Flow Cytometry Core Facility, Faculty of Medical Sciences Newcastle University  Newcastle upon Tyne UK"},{"name":"Biosciences Institute, Innovation, Methodology and Application (IMA) Research Theme, Faculty of Medical Sciences Newcastle University  Newcastle upon Tyne UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"George","family":"Merces","sequence":"additional","affiliation":[{"name":"Biosciences Institute, Innovation, Methodology and Application (IMA) Research Theme, Faculty of Medical Sciences Newcastle University  Newcastle upon Tyne UK"},{"name":"Image Analysis Unit, Faculty of Medical Sciences Newcastle University  Newcastle upon Tyne UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2023,10,5]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1300136110"},{"key":"e_1_2_7_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/cpch.14"},{"key":"e_1_2_7_4_1","doi-asserted-by":"publisher","DOI":"10.1038\/nm.3488"},{"key":"e_1_2_7_5_1","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.2869"},{"key":"e_1_2_7_6_1","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.4397"},{"key":"e_1_2_7_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4939-7346-0_2"},{"key":"e_1_2_7_8_1","doi-asserted-by":"publisher","DOI":"10.1002\/cyto.a.23030"},{"key":"e_1_2_7_9_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-021-01308-y"},{"key":"e_1_2_7_10_1","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.4391"},{"key":"e_1_2_7_11_1","volume-title":"ImcSegmentationPipeline: a pixelclassification based multiplexed image segmentation pipeline","author":"Zanotelli VRT","year":"2017"},{"key":"e_1_2_7_12_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btaa1061"},{"key":"e_1_2_7_13_1","doi-asserted-by":"publisher","DOI":"10.1002\/cyto.a.24535"},{"key":"e_1_2_7_14_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-019-0582-9"},{"key":"e_1_2_7_15_1","doi-asserted-by":"publisher","DOI":"10.1186\/gb-2006-7-10-r100"},{"key":"e_1_2_7_16_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-021-04344-9"},{"key":"e_1_2_7_17_1","doi-asserted-by":"publisher","DOI":"10.3390\/cancers14122916"},{"key":"e_1_2_7_18_1","doi-asserted-by":"publisher","DOI":"10.3389\/fgene.2021.721229"},{"key":"e_1_2_7_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.xpro.2021.101034"},{"key":"e_1_2_7_20_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1008887"},{"key":"e_1_2_7_21_1","article-title":"IMC\u2010Denoise: a content aware denoising pipeline to enhance imaging mass cytometry","author":"Lu P","year":"2022","journal-title":"bioRxiv"},{"key":"e_1_2_7_22_1","doi-asserted-by":"publisher","DOI":"10.1002\/cyto.a.24042"},{"key":"e_1_2_7_23_1","article-title":"Compensation of signal spillover in suspension and imaging mass cytometry","volume":"6","author":"Chevrier S","year":"2018","journal-title":"Cell Syst"},{"key":"e_1_2_7_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2019.2931299"},{"key":"e_1_2_7_25_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-020-01018-x"},{"key":"e_1_2_7_26_1","doi-asserted-by":"publisher","DOI":"10.1002\/cyto.a.22977"},{"key":"e_1_2_7_27_1","doi-asserted-by":"publisher","DOI":"10.1002\/cyto.a.22778"},{"key":"e_1_2_7_28_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1988.10478575"},{"key":"e_1_2_7_29_1","doi-asserted-by":"publisher","DOI":"10.1002\/cyto.a.24491"},{"key":"e_1_2_7_30_1","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-11-546"},{"key":"e_1_2_7_31_1","doi-asserted-by":"publisher","DOI":"10.1002\/cyto.a.24350"},{"key":"e_1_2_7_32_1","doi-asserted-by":"publisher","DOI":"10.1021\/ci030295a"},{"key":"e_1_2_7_33_1","doi-asserted-by":"publisher","DOI":"10.1038\/nbt.4091"},{"key":"e_1_2_7_34_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-019-0619-0"},{"key":"e_1_2_7_35_1","doi-asserted-by":"publisher","DOI":"10.1038\/nbt.4096"},{"key":"e_1_2_7_36_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-018-0308-4"},{"issue":"1","key":"e_1_2_7_37_1","first-page":"1532","article-title":"Understanding how dimension reduction tools work: an empirical approach to deciphering t\u2010SNE, UMAP, TriMap, and PaCMAP for data visualization","volume":"22","author":"Wang Y","year":"2021","journal-title":"Mach Learn Res"},{"key":"e_1_2_7_38_1","volume-title":"TriMap: large\u2010scale dimensionality reduction using triplets Arxiv pre\u2010print","author":"Amid E.","year":"2019"},{"key":"e_1_2_7_39_1","doi-asserted-by":"publisher","DOI":"10.1038\/nbt.4314"},{"key":"e_1_2_7_40_1","doi-asserted-by":"publisher","DOI":"10.1002\/cyto.a.22625"},{"key":"e_1_2_7_41_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-019-1917-7"},{"key":"e_1_2_7_42_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2015.05.047"},{"key":"e_1_2_7_43_1","article-title":"An end\u2010to\u2010end workflow for multiplexed image processing and analysis","author":"Windhager J","year":"2021","journal-title":"bioRxiv"},{"key":"e_1_2_7_44_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0229778"},{"key":"e_1_2_7_45_1","doi-asserted-by":"publisher","DOI":"10.1158\/1078-0432.CCR-20-3340"},{"key":"e_1_2_7_46_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.dib.2021.107090"},{"key":"e_1_2_7_47_1","doi-asserted-by":"publisher","DOI":"10.1038\/s43018-021-00301-w"},{"key":"e_1_2_7_48_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0035693"}],"container-title":["Cytometry Part A"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/cyto.a.24803","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T01:37:13Z","timestamp":1705887433000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/cyto.a.24803"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,5]]},"references-count":47,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2024,1]]}},"alternative-id":["10.1002\/cyto.a.24803"],"URL":"https:\/\/doi.org\/10.1002\/cyto.a.24803","archive":["Portico"],"relation":{"has-review":[{"id-type":"doi","id":"10.1002\/CYTO.A.24803\/v1\/decision1","asserted-by":"object"},{"id-type":"doi","id":"10.1002\/CYTO.A.24803\/v3\/response1","asserted-by":"object"},{"id-type":"doi","id":"10.1002\/CYTO.A.24803\/v1\/review2","asserted-by":"object"},{"id-type":"doi","id":"10.1002\/CYTO.A.24803\/v1\/review1","asserted-by":"object"},{"id-type":"doi","id":"10.1002\/CYTO.A.24803\/v2\/review1","asserted-by":"object"},{"id-type":"doi","id":"10.1002\/CYTO.A.24803\/v2\/response1","asserted-by":"object"},{"id-type":"doi","id":"10.1002\/CYTO.A.24803\/v3\/decision1","asserted-by":"object"},{"id-type":"doi","id":"10.1002\/CYTO.A.24803\/v2\/decision1","asserted-by":"object"}],"has-preprint":[{"id-type":"doi","id":"10.1101\/2023.02.21.526083","asserted-by":"object"}]},"ISSN":["1552-4922","1552-4930"],"issn-type":[{"value":"1552-4922","type":"print"},{"value":"1552-4930","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10,5]]},"assertion":[{"value":"2023-03-28","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-09-18","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-10-05","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}